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Abstract 4366483: Multi-omic Characterization of Clonal Hematopoiesis of Indeterminate Potential (CHIP) in the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) Trials Biorepository

2025· article· en· W4415792934 on OpenAlexaff
Sandhya Rajkumar, Matthew Muller, Paul Sastourne-Haletou, Richard Liu, Farheen Shah, Jiyuan Hu, Claes Held, Iftikhar J. Kullo, Bruce M. McManus, Lars Wallentin, L. Kristin Newby, Mandeep S. Sidhu, Sripal Bangalore, Harmony R. Reynolds, Judith S. Hochman, David J. Maron, Kelly V. Ruggles, Jeffrey S. Berger, Jonathan Newman

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDNA methylationTranscriptomeMethylationDNA microarrayIschemiaGeneHaematopoiesis

Abstract

fetched live from OpenAlex

Introduction/Background: CHIP is a risk factor for cardiovascular (CV) disease, cancer, and all-cause mortality. Previous work has shown that CHIP, and particularly larger CHIP clones, are associated with adverse CV outcomes, yet the molecular pathways through which CHIP impacts CV risk are poorly defined. Hypothesis/Research Question: We hypothesize that the integration of whole blood transcriptomics and methylomics will provide novel insights into the pathophysiology of CHIP. Methods/Approach: Whole blood DNA methylation profiling, transcriptomics, and whole exome sequencing with CHIP calling for variant allele frequencies (VAF) of ≥2% (CHIP) and ≥10% (large CHIP) were performed for 507 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. We identified transcriptomic and methylomic differences between participants with CHIP and large CHIP vs no CHIP using DESeq2 and limma, adjusted for age, sex, and race/ethnicity. Gene set enrichment analysis (GSEA) and probe set enrichment analysis (PSEA) were performed to identify pathway-level alterations in transcription and methylation, respectively. Results/Data: Clinical characteristics of study participants are described in Fig 1A . Compared to no CHIP (n=391), transcriptomics identified 6 differentially expressed genes (DEGs) in CHIP (n=116) and 27 DEGs in large CHIP (n=35) (p-adj<0.05; abs(logFC)>0.25) (Fig 1B) . Compared to no CHIP, methylation identified no differentially methylated probes in CHIP and 6 in large CHIP (padj<0.20, abs(logFC)>0.03). GSEA identified 137 pathways significantly different in both CHIP and large CHIP vs. no CHIP (padj<0.05), while PSEA identified 724 and 2356 pathways (padj<0.20), respectively. Given its stronger relationship with methylation and transcription, downstream analyses focused on large CHIP. Integrating these data, we found 58 pathways to be both hypomethylated and transcriptionally upregulated in large CHIP, including azurophil granule-related pathways implicated in neutrophil degranulation (Fig 1C) . Further investigation into the gene-probe pairs driving the azurophil granule pathway enrichment in large CHIP revealed hypomethylation and increased transcription of genes implicated in neutrophil extracellular trap formation, including ELANE, PTRN3, AZU1, and CTSG (Fig 1D) . Conclusions: Integration of the methylome and transcriptome suggests large CHIP is linked to neutrophil-mediated immune pathways in patients with stable coronary artery disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.334
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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